Browsing Araştırma Çıktıları | WoS | Scopus | TR-Dizin | PubMed by Subject "Classification (of information)"
Now showing items 1-6 of 6
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Analyses of literary texts by using statistical inference methods
(CEUR-WS, 2019)If a road map had to be drawn for Computational Criticism and subsequent Artificial Literature, it would have certainly considered Shakespearean plays. Demonstration of these structures through text analysis can be seen ... -
Benchmark Static API Call Datasets for Malware Family Classification
(Institute of Electrical and Electronics Engineers Inc., 2022)Nowadays, malware and malware incidents are increasing daily, even with various antivirus systems and malware detection or classification methodologies. Machine learning techniques have been the main focus of the security ... -
Breaking the Performance Gap of Fully and Semi-Supervised Learning in Electromagnetic Signature Recognition
(Institute of Electrical and Electronics Engineers Inc., 2023)Intelligent electromagnetic signature recognition is one of the key technologies in Internet-of-Things (IoT) device connection, which can improve system security and speed up the authentication process. In practical ... -
The effect of data augmentation on ADHD diagnostic model using deep learning
(Institute of Electrical and Electronics Engineers Inc., 2019)Attention Deficit Hyperactivity Disorder (ADHD) is a neuro-behavioral hyperactivity disorder. It is frequently seen in childhood and youth, and lasts a lifetime unless treated. The ADHD classification model should be ... -
Reviewing the Effects of Spatial Features on Price Prediction for Real Estate Market: Istanbul Case
(Institute of Electrical and Electronics Engineers Inc., 2022)In the real estate market, spatial features play a crucial role in determining property appraisals and prices. When spatial features are considered, classification techniques have been rarely studied compared to regression, ... -
Simple but effective GRU variants
(Institute of Electrical and Electronics Engineers Inc., 2021)Recurrent Neural Network (RNN) is a widely used deep learning architecture applied to sequence learning problems. However, it is recognized that RNNs suffer from exploding and vanishing gradient problems that prohibit the ...